Corpus Analysis

What is corpus analysis?

Corpus analysis organizes and studies large collections of text, conversations, documents or records. Analysis of vocabulary, sentence patterns, topics, sentiment and semantic relationships reveals recurring content, user needs and potential problems.

• Data preparation and cleaning: remove duplicates, invalid characters, unusable data and sensitive personal information.
• Text feature analysis: measure frequent terms, keywords, sentence length and word combinations.
• Topic and semantic analysis: classify large corpora by topic, intent, sentiment or question type.
• Applying results: build knowledge bases, design support workflows and support model training and evaluation.

How has it developed?

By the first half of 2026, corpus analysis has expanded from word frequencies and keywords to semantic analysis using embeddings, topic clustering and LLMs. Systems can identify semantic relationships between sentences and organize topics, user intents and common questions.

Why use it?

Support conversations, customer feedback, meeting notes, internal documents and product reviews generate large amounts of text. Corpus analysis identifies recurring issues and complaints, organizes internal knowledge and helps build more accurate RAG knowledge bases and training datasets.